In Defense of Portfolio Optimization: What If We Can Forecast?

We challenge the academic consensus that estimation error makes mean–variance portfolio strategies inferior to passive equal-weighted approaches. We demonstrate analytically, via simulation, and empirically that investors endowed with modest forecasting ability benefit substantially from a mean–variance approach. An investor with some forecasting ability improves expected utility by increasing the number of assets considered. We frame our study realistically using budget constraints, transaction costs, and out-of-sample testing for a wide range of investments. We derive practical decision rules to choose between passive and mean–variance optimization and generate results consistent with much financial market practice and the original Markowitz formulation.Disclosure: The authors report no conflicts of interest. Editor’s Note:This article was externally reviewed using our double-blind peer-review process. When the article was accepted for publication, the authors thanked the reviewers in their acknowledgments. Nick Baltas was one of the reviewers for this article.Submitted 8 June 2018Accepted 20 March 2019 by Stephen J. Brown.